Research classified by Journal of Economic Literature (JEL) codes

1. Nowcasting
2. Bayesian Vector autoregressions (BVARs)
3. Dynamic Factor Models

2024

• Pesaran, M. H. & Smith, R. P., 2024, "High-Dimensional Forecasting with Known Knowns and Known Unknowns," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2406, Feb.
• Vainora, J., 2026, "Asymptotic Theory Under Network Stationarity," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2439, Jan.
• Vainora, J., 2024, "Latent Position-Based Modeling of Parameter Heterogeneity," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2455, Oct.
• Pesaran, M. H. & Song, H., 2024, "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2464, Oct.
• Linton, O. B. & Rücker, M. & Vogt, M. & Walsh, C., 2024, "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects," Cambridge Working Papers in Economics, Faculty of Economics, University of Cambridge, number 2467, Nov.
• Ritesh Patel & Anand Kumar Mishra & Muhammad Zubair Chishti & Tejas M. Modi, 2024, "Relationship Between Internet Banking Service Quality, e-Customer Satisfaction, and Loyalty: A Comparative Study of India and Pakistan," Journal of Central Banking Theory and Practice, Central bank of Montenegro, volume 13, issue 2, pages 213-228.
• Jennifer Bernard & Kelsey Drotning & Katie R. Genadek, 2024, "Where Are Your Parents? Exploring Potential Bias in Administrative Records on Children," Working Papers, Center for Economic Studies, U.S. Census Bureau, number 24-18, Mar.
• Thiemo Fetzer & Callum Shaw & Jacob Edenhofer, 2024, "Informational Boundaries of the State," CESifo Working Paper Series, CESifo, number 10901.
• M. Hashem Pesaran & Ron P. Smith, 2024, "High-Dimensional Forecasting with Known Knowns and Known Unknowns," CESifo Working Paper Series, CESifo, number 10931.
• Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024, "Inference for Regression with Variables Generated from Unstructured Data," CESifo Working Paper Series, CESifo, number 11119.
• Thomas Fackler & Oliver Falck & Moritz Goldbeck & Fabian Hans & Annina Hering, 2024, "The Greener, the Higher: Labor Demand of Automotive Firms during the Green Transformation," CESifo Working Paper Series, CESifo, number 11160.
• M. Hashem Pesaran & Hayun Song, 2024, "Forecasting 2024 US Presidential Election by States Using County Level Data: Too Close to Call," CESifo Working Paper Series, CESifo, number 11415.
• M. Hashem Pesaran & Yimeng Xie, 2024, "How to Detect Network Dependence in Latent Factor Models? A Bias-Corrected CD Test," CESifo Working Paper Series, CESifo, number 11470.
• Mariia Okuneva & Philipp Hauber & Kai Carstensen & Jasper Bär, 2024, "Nowcasting German GDP with Text Data," CESifo Working Paper Series, CESifo, number 11587.
• Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024, "Informational Boundaries of the State," CAGE Online Working Paper Series, Competitive Advantage in the Global Economy (CAGE), number 697.
• Matthias R. Fengler & Minh Tri Phan, 2024, "Unveiling Themes in 10-K Disclosures: A New Topic Modeling Perspective," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-106, Oct.
• Francesco Audrino & Jessica Gentner & Simon Stalder, 2024, "Quantifying Uncertainty: A New Era of Measurement through Large Language Models," Swiss Finance Institute Research Paper Series, Swiss Finance Institute, number 24-68, Aug.
• Francisco Peñaranda & Enrique Sentana, 2024, "Portfolio management with big data," Working Papers, CEMFI, number wp2024_2411, Jun.
• Guberney Muñetón Santa & Carlos Andrés Pérez Aguirre & Juan Rafael Orozco-Arroyave, 2024, "Identificación de la pobreza en Colombia: Comparación entre el índice de pobreza multidimensional y el sistema de identificación de beneficiarios de programas sociales," Revista Desarrollo y Sociedad, Universidad de los Andes,Facultad de Economía, CEDE, volume 98, issue 3, pages 45-68.
• Juan David Valencia-Beltrán, 2024, "Dynamics of Regional Business Cycles in Colombian Cities: Identification of Growth Rates, Recession Propagation, and Cluster Analysis," Revista de Economía del Rosario, Universidad del Rosario, volume 27, issue 1, pages 1-45, DOI: 10.12804/revistas.urosario.edu.co/e.
• Pavel Vidal & Lya Paola Sierra-Suárez & Julieth Cerón, 2024, "Indicator for the Regional Labor Market Using Machine Learning Techniques: Application to Colombian Cities," Revista de Economía del Rosario, Universidad del Rosario, volume 27, issue 1, pages 1-31, DOI: 10.12804/revistas.urosario.edu.co/e.
• Fetzer, Thiemo & Shaw, Callum & Edenhofer, Jacob, 2024, "Informational Boundaries of the State," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 18773, Jan.
• Battaglia, Laura & Christensen, Tim & Hansen, Stephen & Sacher, Szymon, 2024, "Inference for Regression with Variables Generated from Unstructured Data," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19115, May.
• Penaranda, Francisco & Sentana, Enrique, 2024, "Portfolio management with big data," CEPR Discussion Papers, C.E.P.R. Discussion Papers, number 19314, Jul.
• Garrón Vedia, Ignacio & Rodríguez Caballero, Carlos Vladimir & Ruiz Ortega, Esther, 2024, "International vulnerability of inflation," DES - Working Papers. Statistics and Econometrics. WS, Universidad Carlos III de Madrid. Departamento de Estadística, number 44814, Nov.
• Filippou, Ilias & Taylor, Mark P. & Wang, Zigan, 2024, "Media Sentiment and Currency Reversals," Journal of Financial and Quantitative Analysis, Cambridge University Press, volume 59, issue 3, pages 1401-1429, May.
• Pesaran, M. Hashem & Smith, Ron P., 2024, "High-Dimensional Forecasting With Known Knowns And Known Unknowns," National Institute Economic Review, National Institute of Economic and Social Research, volume 267, issue , pages 1-25, February.
• Jin Seo Cho & Peter C. B. Phillips, 2024, "GMM Estimation with Brownian Kernels Applied to Income Inequality Measurement," Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, number 2411, Oct.
• Richard Schnorrenberger & Aishameriane Schmidt & Guilherme Valle Moura, 2024, "Harnessing Machine Learning for Real-Time Inflation Nowcasting," Working Papers, DNB, number 806, Mar.
• Lo Duca, Marco & Moccero, Diego & Parlapiano, Fabio, 2024, "The impact of macroeconomic and monetary policy shocks on credit risk in the euro area corporate sector," Working Paper Series, European Central Bank, number 2897, Jan.
• Allayioti, Anastasia & Venditti, Fabrizio, 2024, "The role of comovement and time-varying dynamics in forecasting commodity prices," Working Paper Series, European Central Bank, number 2901, Feb.
• Beck, Günter W. & Carstensen, Kai & Menz, Jan-Oliver & Schnorrenberger, Richard & Wieland, Elisabeth, 2024, "Nowcasting consumer price inflation using high-frequency scanner data: evidence from Germany," Working Paper Series, European Central Bank, number 2930, Apr.
• Audoly, Richard & Paz-Pardo, Gonzalo & McGee, Rory & Ocampo, Sergio, 2024, "The life-cycle dynamics of wealth mobility," Working Paper Series, European Central Bank, number 2976, Aug.
• Linzenich, Jan & Meunier, Baptiste, 2024, "Nowcasting Made Easier: a toolbox for economists," Working Paper Series, European Central Bank, number 3004, Dec.
• Restu Arisanti & Suci Purnamawati & Agus Muslim, 2024, "Determinants of Greenhouse Gas Emissions in the Transportation Sector in Indonesia: Official Statistics and Big Data Approach," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 1, pages 86-97, January.
• Farrukh Nawaz Kayani & Ismat Nasim & Khalil Abu Saleem, 2024, "Analyzing the Impact of Governance, Environment and Trade on Inward FDI: A Case of Cambodia, Thailand and Vietnam from ASEAN," International Journal of Energy Economics and Policy, Econjournals, volume 14, issue 2, pages 523-534, March.
• Trapati Narwaria & Rajiv Dwivedi & Anil Vashisht & Apoorva Mishra & Pratiksha Saxena & Vivek Gupta & Abhishek Singhal & Sandeep Raghuwanshi, 2024, "A Bibliometric Analysis of Employee Turnover Intention among IT Sector Employees," International Review of Management and Marketing, Econjournals, volume 14, issue 6, pages 355-363, October.
• Klieber, Karin, 2024, "Non-linear dimension reduction in factor-augmented vector autoregressions," Journal of Economic Dynamics and Control, Elsevier, volume 159, issue C, DOI: 10.1016/j.jedc.2023.104800.
• Ismail, I. & Stam, P.J.A. & Portrait, F.R.M. & van Witteloostuijn, A. & Koolman, X., 2024, "Addressing unanticipated interactions in risk equalization: A machine learning approach to modeling medical expenditure risk," Economic Modelling, Elsevier, volume 130, issue C, DOI: 10.1016/j.econmod.2023.106564.
• Delogu, Marco & Lagravinese, Raffaele & Paolini, Dimitri & Resce, Giuliano, 2024, "Predicting dropout from higher education: Evidence from Italy," Economic Modelling, Elsevier, volume 130, issue C, DOI: 10.1016/j.econmod.2023.106583.
• Ren, Tingting & Li, Shaofang & Zhang, Siying, 2024, "Stock market extreme risk prediction based on machine learning: Evidence from the American market," The North American Journal of Economics and Finance, Elsevier, volume 74, issue C, DOI: 10.1016/j.najef.2024.102241.
• Hadji-Lazaro, Paul & Salin, Mathilde & Svartzman, Romain & Espagne, Etienne & Gauthey, Julien & Berger, Joshua & Calas, Julien & Godin, Antoine & Vallier, Antoine, 2024, "Biodiversity loss and financial stability as a new frontier for central banks: An exploration for France," Ecological Economics, Elsevier, volume 223, issue C, DOI: 10.1016/j.ecolecon.2024.108246.
• Dubbert, Tore & Kempa, Bernd, 2024, "Nowcasting the output gap with shadow rates," Economics Letters, Elsevier, volume 236, issue C, DOI: 10.1016/j.econlet.2024.111583.
• Ballinari, Daniele, 2024, "Calibrating doubly-robust estimators with unbalanced treatment assignment," Economics Letters, Elsevier, volume 241, issue C, DOI: 10.1016/j.econlet.2024.111838.
• Kunaschk, Max, 2024, "Enriching administrative data using survey data and machine learning techniques," Economics Letters, Elsevier, volume 243, issue C, DOI: 10.1016/j.econlet.2024.111924.
• Lim, Dennis & Wang, Wenjie & Zhang, Yichong, 2024, "A conditional linear combination test with many weak instruments," Journal of Econometrics, Elsevier, volume 238, issue 2, DOI: 10.1016/j.jeconom.2023.105602.
• Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024, "The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, volume 238, issue 2, DOI: 10.1016/j.jeconom.2023.105631.
• Reuvers, Hanno & Wijler, Etienne, 2024, "Sparse generalized Yule–Walker estimation for large spatio-temporal autoregressions with an application to NO2 satellite data," Journal of Econometrics, Elsevier, volume 239, issue 1, DOI: 10.1016/j.jeconom.2023.105520.
• Chang, Jinyuan & Hu, Qiao & Liu, Cheng & Tang, Cheng Yong, 2024, "Optimal covariance matrix estimation for high-dimensional noise in high-frequency data," Journal of Econometrics, Elsevier, volume 239, issue 2, DOI: 10.1016/j.jeconom.2022.06.010.
• Fan, Qingliang & Wu, Ruike & Yang, Yanrong & Zhong, Wei, 2024, "Time-varying minimum variance portfolio," Journal of Econometrics, Elsevier, volume 239, issue 2, DOI: 10.1016/j.jeconom.2022.08.007.
• Chang, Jinyuan & Chen, Cheng & Qiao, Xinghao & Yao, Qiwei, 2024, "An autocovariance-based learning framework for high-dimensional functional time series," Journal of Econometrics, Elsevier, volume 239, issue 2, DOI: 10.1016/j.jeconom.2023.01.007.
• Wan, Runzhe & Li, Yingying & Lu, Wenbin & Song, Rui, 2024, "Mining the factor zoo: Estimation of latent factor models with sufficient proxies," Journal of Econometrics, Elsevier, volume 239, issue 2, DOI: 10.1016/j.jeconom.2022.08.013.
• Chen, Dachuan & Mykland, Per A. & Zhang, Lan, 2024, "Realized regression with asynchronous and noisy high frequency and high dimensional data," Journal of Econometrics, Elsevier, volume 239, issue 2, DOI: 10.1016/j.jeconom.2023.02.015.
• Choi, Jungjun & Kwon, Hyukjun & Liao, Yuan, 2024, "Inference for low-rank completion without sample splitting with application to treatment effect estimation," Journal of Econometrics, Elsevier, volume 240, issue 1, DOI: 10.1016/j.jeconom.2024.105682.
• Loaiza-Maya, Rubén & Nibbering, Didier & Zhu, Dan, 2024, "Hybrid unadjusted Langevin methods for high-dimensional latent variable models," Journal of Econometrics, Elsevier, volume 241, issue 2, DOI: 10.1016/j.jeconom.2024.105741.
• Urga, Giovanni & Wang, Fa, 2024, "Estimation and inference for high dimensional factor model with regime switching," Journal of Econometrics, Elsevier, volume 241, issue 2, DOI: 10.1016/j.jeconom.2024.105752.
• Mei, Ziwei & Shi, Zhentao, 2024, "On LASSO for high dimensional predictive regression," Journal of Econometrics, Elsevier, volume 242, issue 2, DOI: 10.1016/j.jeconom.2024.105809.
• Hou, Chenghan, 2024, "Large Bayesian SVARs with linear restrictions," Journal of Econometrics, Elsevier, volume 244, issue 1, DOI: 10.1016/j.jeconom.2024.105850.
• Duan, Junting & Pelger, Markus & Xiong, Ruoxuan, 2024, "Target PCA: Transfer learning large dimensional panel data," Journal of Econometrics, Elsevier, volume 244, issue 2, DOI: 10.1016/j.jeconom.2023.105521.
• Bai, Jushan & Duan, Jiangtao & Han, Xu, 2024, "Reprint of: The likelihood ratio test for structural changes in factor models," Journal of Econometrics, Elsevier, volume 244, issue 2, DOI: 10.1016/j.jeconom.2024.105745.
• Chudik, Alexander & Pesaran, M. Hashem & Sharifvaghefi, Mahrad, 2024, "Variable selection in high dimensional linear regressions with parameter instability," Journal of Econometrics, Elsevier, volume 246, issue 1, DOI: 10.1016/j.jeconom.2024.105900.
• Ahelegbey, Daniel Felix & Billio, Monica & Casarin, Roberto, 2024, "Modeling Turning Points in the Global Equity Market," Econometrics and Statistics, Elsevier, volume 30, issue C, pages 60-75, DOI: 10.1016/j.ecosta.2021.10.004.
• Montorsi, Carlotta & Fusco, Alessio & Van Kerm, Philippe & Bordas, Stéphane P.A., 2024, "Predicting depression in old age: Combining life course data with machine learning," Economics & Human Biology, Elsevier, volume 52, issue C, DOI: 10.1016/j.ehb.2023.101331.
• Sun, Chuanping, 2024, "Factor correlation and the cross section of asset returns: A correlation-robust machine learning approach," Journal of Empirical Finance, Elsevier, volume 77, issue C, DOI: 10.1016/j.jempfin.2024.101497.
• Trimborn, Simon & Peng, Hanqiu & Chen, Ying, 2024, "Influencer detection meets network autoregression — Influential regions in the bitcoin blockchain," Journal of Empirical Finance, Elsevier, volume 78, issue C, DOI: 10.1016/j.jempfin.2024.101529.
• Ouyang, Zisheng & Lu, Min & Ouyang, Zhongzhe & Zhou, Xuewei & Wang, Ren, 2024, "A novel integrated method for improving the forecasting accuracy of crude oil: ESMD-CFastICA-BiLSTM-Attention," Energy Economics, Elsevier, volume 138, issue C, DOI: 10.1016/j.eneco.2024.107851.
• Yang, Kun & Sun, Yuying & Hong, Yongmiao & Wang, Shouyang, 2024, "Forecasting interval carbon price through a multi-scale interval-valued decomposition ensemble approach," Energy Economics, Elsevier, volume 139, issue C, DOI: 10.1016/j.eneco.2024.107952.
• Hwang, Sam Il Myoung & Squires, Munir, 2024, "Linked samples and measurement error in historical US census data," Explorations in Economic History, Elsevier, volume 93, issue C, DOI: 10.1016/j.eeh.2024.101579.
• Karim, Sitara & Shafiullah, Muhammad & Naeem, Muhammad Abubakr, 2024, "When one domino falls, others follow: A machine learning analysis of extreme risk spillovers in developed stock markets," International Review of Financial Analysis, Elsevier, volume 93, issue C, DOI: 10.1016/j.irfa.2024.103202.
• Moffo, Ahmadou Mustapha Fonton, 2024, "A machine learning approach in stress testing US bank holding companies," International Review of Financial Analysis, Elsevier, volume 95, issue PC, DOI: 10.1016/j.irfa.2024.103476.
• Cakici, Nusret & Zaremba, Adam, 2024, "What drives stock returns across countries? Insights from machine learning models," International Review of Financial Analysis, Elsevier, volume 96, issue PA, DOI: 10.1016/j.irfa.2024.103569.
• Jing, Zhongbo & Li, Qin & Zhao, Hongyi & Zhao, Yang, 2024, "Predicting stock price crash risk in China: A modified graph WaveNet model," Finance Research Letters, Elsevier, volume 64, issue C, DOI: 10.1016/j.frl.2024.105468.
• Bang, Jeongseok & Kang, Yeonchan & Ryu, Doojin, 2024, "Potential pricing factors in the Korean market," Finance Research Letters, Elsevier, volume 67, issue PB, DOI: 10.1016/j.frl.2024.105946.
• Huang, Xirong & Geng, Chen & Li, Xiuting & Dong, Jichang, 2024, "Multiple factor flows and heterogeneous premium of urban house prices: Empirical evidence from Chinese cities," Finance Research Letters, Elsevier, volume 69, issue PB, DOI: 10.1016/j.frl.2024.106287.
• Ashwin, Julian, 2024, "Financial news media and volatility: Is there more to newspapers than news?," Journal of Financial Markets, Elsevier, volume 69, issue C, DOI: 10.1016/j.finmar.2024.100896.
• Kim, Hyeongwoo & Son, Jisoo, 2024, "What charge-off rates are predictable by macroeconomic latent factors?," Journal of Financial Stability, Elsevier, volume 74, issue C, DOI: 10.1016/j.jfs.2024.101301.
• Nicodemo, Catia & Orso, Cristina E. & Tealdi, Cristina, 2024, "Overseas general practitioners (GPs) and prescription behaviour in England," Health Policy, Elsevier, volume 140, issue C, DOI: 10.1016/j.healthpol.2023.104967.
• Shemendyuk, Aleksandr & Wagner, Joël, 2024, "On the factors determining the health profiles and care needs of institutionalized elders," Insurance: Mathematics and Economics, Elsevier, volume 114, issue C, pages 223-241, DOI: 10.1016/j.insmatheco.2023.12.003.
• Ungolo, Francesco & van den Heuvel, Edwin R., 2024, "A Dirichlet process mixture regression model for the analysis of competing risk events," Insurance: Mathematics and Economics, Elsevier, volume 116, issue C, pages 95-113, DOI: 10.1016/j.insmatheco.2024.02.004.
• Coulibaly, Issiaka & Dembélé, Moustapha, 2024, "Impacts of remittances from internal and international migrants on poverty and inequality in Mali," International Economics, Elsevier, volume 177, issue C, DOI: 10.1016/j.inteco.2024.100482.
• Crispino, Marta & Conteduca, Francesco Paolo, 2024, "It's a match! Linking foreign counterparts in Italian customs data to their balance sheets," International Economics, Elsevier, volume 179, issue C, DOI: 10.1016/j.inteco.2024.100511.
• Joseph, Andreas & Potjagailo, Galina & Chakraborty, Chiranjit & Kapetanios, George, 2024, "Forecasting UK inflation bottom up," International Journal of Forecasting, Elsevier, volume 40, issue 4, pages 1521-1538, DOI: 10.1016/j.ijforecast.2024.01.001.
• Furukawa, Kakuho & Hisano, Ryohei & Minoura, Yukio & Yagi, Tomoyuki, 2024, "A nowcasting model of industrial production using alternative data and machine learning approaches," Japan and the World Economy, Elsevier, volume 71, issue C, DOI: 10.1016/j.japwor.2024.101271.
• Kurz, Konstantin & Bock, Carolin & Hanschur, Leonard, 2024, "Flip the tweet – the two-sided coin of entrepreneurial empathy and its ambiguous influence on new product development," Journal of Business Venturing, Elsevier, volume 39, issue 2, DOI: 10.1016/j.jbusvent.2023.106378.
• Bekaert, Els & Constant, Amelie F. & Foubert, Killian & Ruyssen, Ilse, 2024, "Longing for which home: A global analysis of the determinants of aspirations to stay, return or migrate onwards," Journal of Economic Behavior & Organization, Elsevier, volume 219, issue C, pages 564-587, DOI: 10.1016/j.jebo.2024.02.001.
• Nguyen, Ha Minh, 2024, "Beyond the annual averages: Impact of seasonal temperature on employment growth in US counties," Journal of Environmental Economics and Management, Elsevier, volume 125, issue C, DOI: 10.1016/j.jeem.2024.102946.
• Ardia, David & Barras, Laurent & Gagliardini, Patrick & Scaillet, Olivier, 2024, "Is it alpha or beta? Decomposing hedge fund returns when models are misspecified," Journal of Financial Economics, Elsevier, volume 154, issue C, DOI: 10.1016/j.jfineco.2024.103805.
• Cao, Sean & Jiang, Wei & Wang, Junbo & Yang, Baozhong, 2024, "From Man vs. Machine to Man + Machine: The art and AI of stock analyses," Journal of Financial Economics, Elsevier, volume 160, issue C, DOI: 10.1016/j.jfineco.2024.103910.
• Tabe-Ojong, Martin Paul Jr. & Nana, Ibrahim & Zimmermann, Andrea & Jafari, Yaghoob, 2024, "Trends and evolution of global value chains in food and agriculture: Implications for food security and nutrition," Food Policy, Elsevier, volume 127, issue C, DOI: 10.1016/j.foodpol.2024.102679.
• Gerba, Eddie & Leiva-León, Danilo & Rubio, Margarita, 2024, "Inspecting cross-border macro-financial mechanisms," Journal of International Money and Finance, Elsevier, volume 145, issue C, DOI: 10.1016/j.jimonfin.2024.103094.
• Sen, Abhibasu & Dutta Choudhury, Karabi, 2024, "Forecasting the Crude Oil prices for last four decades using deep learning approach," Resources Policy, Elsevier, volume 88, issue C, DOI: 10.1016/j.resourpol.2023.104438.
• Noailly, Joëlle & Nowzohour, Laura & van den Heuvel, Matthias & Pla, Ireneu, 2024, "Heard the news? Environmental policy and clean investments," Journal of Public Economics, Elsevier, volume 238, issue C, DOI: 10.1016/j.jpubeco.2024.105190.
• Galiani, Sebastian & Quistorff, Brian, 2024, "Assessing external validity in practice," Research in Economics, Elsevier, volume 78, issue 3, DOI: 10.1016/j.rie.2024.100964.
• du Plessis, Emile, 2024, "Reading between the lines: Quantitative text analysis of banking crises," Research in Economics, Elsevier, volume 78, issue 4, DOI: 10.1016/j.rie.2024.101000.
• Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024, "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, volume 93, issue PB, pages 673-711, DOI: 10.1016/j.iref.2024.05.008.
• Hausladen, Carina I. & Fochmann, Martin & Mohr, Peter, 2024, "Predicting compliance: Leveraging chat data for supervised classification in experimental research," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, volume 109, issue C, DOI: 10.1016/j.socec.2024.102164.
• Atsebi, Jean-Marc B. & Ouedraogo, Rasmane & Séri-Atsebi, Regina, 2024, "Mining for delinking children’s occupation to that of their parents in Africa," World Development, Elsevier, volume 184, issue C, DOI: 10.1016/j.worlddev.2024.106722.
• Roshen Fernando, 2024, "Global Economic Impacts of Physical Climate Risks on Agriculture and Energy," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-37, Jun.
• Roshen Fernando, 2024, "Impact of Physical Climate Risks on Financial Assets," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-38, Jun.
• Roshen Fernando & Warwick McKibbin, 2024, "Global Economic Impacts of Antimicrobial Resistance," CAMA Working Papers, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University, number 2024-41, Jun.
• Aristide Houndetoungan & Abdoul Haki Maoude, 2024, "Inference for Two-Stage Extremum Estimators," Thema Working Papers, THEMA (Théorie Economique, Modélisation et Applications), CY Cergy-Paris University, ESSEC and CNRS, number 2024-01.
• Guillermo Cabanillas-Jiménez, 2024, "Testing the permanent income hypothesis using the Spanish Christmas Lottery," Applied Economic Analysis, Emerald Group Publishing Limited, volume 32, issue 96, pages 232-259, May, DOI: 10.1108/AEA-07-2023-0276.
• Prince Kumar Maurya & Rohit Bansal & Anand Kumar Mishra, 2024, "Dynamic connectedness among market volatilities: a perspective of COVID-19 and Russia-Ukraine conflict," Studies in Economics and Finance, Emerald Group Publishing Limited, volume 41, issue 5, pages 1119-1140, April, DOI: 10.1108/SEF-01-2024-0029.
• Meilian ZHANG & Ting YIN & Emiko USUI & Takashi OSHIO & Yi ZHANG, 2024, "Unraveling the Determinants of Overemployment and Underemployment among Older Workers in Japan: A machine learning approach," Discussion papers, Research Institute of Economy, Trade and Industry (RIETI), number 24034, Mar.
• Lenka Nechvatalova, 2024, "Multi-Horizon Equity Returns Predictability via Machine Learning," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, volume 74, issue 2, pages 142-190, May.
• Lenka Nechvatalova, 2024, "Autoencoder Asset Pricing Models and Economic Restrictions - International Evidence," Working Papers IES, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, number 2024/26, Aug, revised Aug 2024.
• Celso Brunetti & Matthew Carl & Jacob Gerszten & Chiara Scotti & Chaehee Shin, 2024, "Interconnectedness in the Corporate Bond Market," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2024-066, Aug, DOI: 10.17016/FEDS.2024.066.
• Matteo Barigozzi & Matteo Luciani, 2024, "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2024-086, Oct, DOI: 10.17016/FEDS.2024.086.
• Matteo Barigozzi & Claudio Lissona & Matteo Luciani, 2024, "Measuring the Euro Area Output Gap," Finance and Economics Discussion Series, Board of Governors of the Federal Reserve System (U.S.), number 2024-099, Dec, DOI: 10.17016/FEDS.2024.099.
• Tarek A. Hassan & Stephan Hollander & Aakash Kalyani & Markus Schwedeler & Ahmed Tahoun & Laurence van Lent, 2024, "Text as Data in Economic Analysis," Working Papers, Federal Reserve Bank of St. Louis, number 2024-022, Sep, revised 11 Sep 2025, DOI: 10.20955/wp.2024.022.
• Prodosh Eugene Simlai, 2024, "Risk Characterization of Firms with ESG Attributes Using a Supervised Machine Learning Method," JRFM, MDPI, volume 17, issue 5, pages 1-9, May.
• Tetiana Yukhymenko & Oleh Sorochan, 2024, "Impact of the central bank's communication on macro financial outcomes," IHEID Working Papers, Economics Section, The Graduate Institute of International Studies, number 01-2024, Feb.
• Christophe Hurlin & Christophe Pérignon & Sébastien Saurin, 2024, "The Fairness of Credit Scoring Models," Post-Print, HAL, number hal-04787960, Nov, DOI: 10.1287/mnsc.2022.03888.
• Jérôme Dugast & Thierry Foucault, 2024, "Equilibrium Data Mining and Data Abundance," Post-Print, HAL, number hal-04941346, Oct, DOI: 10.1111/jofi.13397.
• Els Bekaert & Amelie Constant & Killian Foubert & Ilse Ruyssen, 2024, "Longing for which home: A global analysis of the determinants of aspirations to stay, return or migrate onwards," Post-Print, HAL, number hal-04951541, Mar, DOI: 10.1016/j.jebo.2024.02.001.
• Odran Bonnet & François Le Grand & Tom Olivia & Xavier Ragot & Lionel Wilner, 2024, "The consumption response to unemployment : evidence from French bank account data
  [Lorsqu’ils perdent leur emploi, les ménages puisent-ils dans leur épargne ou réduisent-ils leurs dépenses ? – une approche par des données de comptes bancaires]," Sciences Po Economics Publications (main), HAL, number hal-05316543, Oct.
• Odran Bonnet & François Le Grand & Tom Olivia & Xavier Ragot & Lionel Wilner, 2024, "The consumption response to unemployment : evidence from French bank account data
  [Lorsqu’ils perdent leur emploi, les ménages puisent-ils dans leur épargne ou réduisent-ils leurs dépenses ? – une approche par des données de comptes bancaires]," Working Papers, HAL, number hal-05316543, Oct.
• Dalloul, Ami, 2024, "The Fed Speaks, but does the Press Repeat? Investigating the Communication Channel between the Fed and the Written Press," Hannover Economic Papers (HEP), Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät, number dp-724, Aug.
• Christian Møller Dahl & Torben Johansen & Christian Vedel, 2024, "Breaking the HISCO Barrier: Automatic Occupational Standardization with OccCANINE," Working Papers, European Historical Economics Society (EHES), number 0255, Apr.
• Bertsch, Christoph & Hull, Isaiah & Lumsdaine, Robin L. & Zhang, Xin, 2024, "Four Facts about International Central Bank Communication," Working Paper Series, Sveriges Riksbank (Central Bank of Sweden), number 432, Mar.
• Berg, Gerard J. van den & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2024, "Predicting Re-Employment: Machine Learning Versus Assessments by Unemployed Workers and by Their Caseworkers," IAB-Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], number 202403, Feb, DOI: 10.48720/IAB.DP.2403.
• Mühlbauer, Sabrina & Weber, Enzo, 2024, "Predicting Job Match Quality: A Machine Learning Approach," IAB-Discussion Paper, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], number 202409, Jul, DOI: 10.48720/IAB.DP.2409.
• Elok Heniwati & Angga Hervianto, 2024, "Logistic Regression to Predict BPK's Audit Opinion," Oblik i finansi, Institute of Accounting and Finance, issue 2, pages 118-127, June, DOI: 10.33146/2307-9878-2024-2(104)-118-.
• Bjarni G. Einarsson, 2024, "Online Monitoring of Policy Optimality," Economics, Department of Economics, Central bank of Iceland, number wp95, Apr.
• Wishnu Badrawani & Citra Amanda & MHA Ridhwan & Novi Maryaningsih & Faizal Kurniawan & Irfan Sampe & Renardi Ardiya Bimantoro & Maulana Ryan Nurfadhila, 2024, "Indeks Konsumsi/Pembayaran Nasional (Ikpn): Proksi Konsumsi Rumah Tangga Berbasis Data Sistem Pembayaran," Working Papers, Bank Indonesia, number WP/13/2024.
• Surabhi Garg & Srijit Mishra, 2024, "Effect of demand and supply side factors on school education outcomes in India," Indira Gandhi Institute of Development Research, Mumbai Working Papers, Indira Gandhi Institute of Development Research, Mumbai, India, number 2024-013, Jul.
• Catalina Bolancé & Montserrat Guillen & Ana M. Pérez-Marín & Anna-Patrícia Orteu, 2024, "Difference-in-Difference models to estimate causal effects on auto insurers behavior," IREA Working Papers, University of Barcelona, Research Institute of Applied Economics, number 202411, Feb, revised Feb 2024.
• Ahrens, Achim & Hansen, Christian B. & Schaffer, Mark E & Wiemann, Thomas, 2024, "Model Averaging and Double Machine Learning," IZA Discussion Papers, IZA Network @ LISER, number 16714, Jan.
• Lee, Wang-Sheng & Tran, Trang My, 2024, "Emissions from Military Training: Evidence from Australia," IZA Discussion Papers, IZA Network @ LISER, number 16889, Mar.
• Kumar, Pradeep & Nicodemo, Catia & Oreffice, Sonia & Quintana-Domeque, Climent, 2024, "Machine Learning and Multiple Abortions," IZA Discussion Papers, IZA Network @ LISER, number 17046, Jun.
• Barbaglia, Luca & Bellia, Mario & Di Girolamo, Francesca & Rho, Caterina, 2024, "Crypto news and policy innovations: Are European markets affected?," JRC Working Papers in Economics and Finance, Joint Research Centre, European Commission, number 2024-07, Nov.
• Zongwu Cai & Pixiong Chen, 2024, "Online Investor Sentiment via Machine Learning," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS, University of Kansas, Department of Economics, number 202411, Sep, revised Sep 2024.
• Yamin Ahmad & Adam Check & Ming Chien Lo, 2024, "Unit Roots in Macroeconomic Time Series: A Comparison of Classical, Bayesian and Machine Learning Approaches," Computational Economics, Springer;Society for Computational Economics, volume 63, issue 6, pages 2139-2173, June, DOI: 10.1007/s10614-023-10397-0.
• Rama K. Malladi, 2024, "Benchmark Analysis of Machine Learning Methods to Forecast the U.S. Annual Inflation Rate During a High-Decile Inflation Period," Computational Economics, Springer;Society for Computational Economics, volume 64, issue 1, pages 335-375, July, DOI: 10.1007/s10614-023-10436-w.
• Ghislain Geniaux, 2024, "Speeding up estimation of spatially varying coefficients models," Journal of Geographical Systems, Springer, volume 26, issue 3, pages 293-327, July, DOI: 10.1007/s10109-024-00442-3.
• Muhammad Asad & Saeed Akbar & Sabur Mollah, 2024, "The role of independent directors’ tenure and network in controlling real-earnings management practices," Review of Quantitative Finance and Accounting, Springer, volume 63, issue 4, pages 1251-1279, November, DOI: 10.1007/s11156-024-01288-y.
• Karolis Matikonis & Matthew Gobey, 2024, "Small Business Property Tax Reductions and Firm Productivity," Small Business Economics, Springer, volume 62, issue 1, pages 307-324, January, DOI: 10.1007/s11187-023-00768-0.
• Marie Madeleine Meurer & Maksim Belitski & Christian Fisch & Roy Thurik, 2024, "What gets published and what doesn’t? Exploring optimal distinctiveness and diverse expectations in entrepreneurship articles," Small Business Economics, Springer, volume 63, issue 3, pages 1139-1170, October, DOI: 10.1007/s11187-023-00865-0.
• Bachmann Ronald & Boockmann Bernhard & Vonnahme Christina & Wiemann Jan Simon, 2024, "Internationale Dateninnovationen: Potenziale für die deutsche Arbeitsmarkt- und Sozialpolitik," Zeitschrift für Wirtschaftspolitik, De Gruyter, volume 73, issue 1, pages 1-23, May, DOI: 10.1515/zfwp-2024-2001.
• Albina Latifi & David Lenz & Peter Winker, 2024, "Identification of Innovation Drivers Based on Technology-Related News Articles," MAGKS Papers on Economics, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung), number 202401, Jan.
• Jenny Bethäuser, 2024, "Impact of Policy Measures and Behavior on the COVID Pandemic in Germany," MAGKS Papers on Economics, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung), number 202411, Jun.
• Paulo Barbosa & João Cortes & João Amador, 2024, "Distance to Export: A Machine Learning Approach with Portuguese Firms," GEE Papers, Gabinete de Estratégia e Estudos, Ministério da Economia, number 182, Jul, revised Jul 2024.
• Asia J. Biega, 2024, "Data Repurposing through Compatibility: A Computational Perspective," Journal of Institutional and Theoretical Economics (JITE), Mohr Siebeck, Tübingen, volume 180, issue 2, pages 368-392, DOI: 10.1628/jite-2024-0017.
• Piroska Nagy Mohacsi & Tatiana Evdokimova & Olga Ponomarenko & Elina Ribakova, 2024, "Emerging Market Central Banking and Communication: The Great Catchup," Financial and Economic Review, Magyar Nemzeti Bank (Central Bank of Hungary), volume 23, issue 1, pages 29-49.
• Degui Li & Bin Peng & Songqiao Tang & Weibiao Wu, 2024, "Estimation of Grouped Time-Varying Network Vector Autoregression Models," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 6/24.
• James D. Hamilton & Xinwei Ma & Jin Xi, 2024, "Principal Component Analysis for a Mix of Stationary and Nonstationary Variables," NBER Working Papers, National Bureau of Economic Research, Inc, number 32068, Jan.
• Yi Chen & Hanming Fang & Yi Zhao & Zibo Zhao, 2024, "Recovering Overlooked Information in Categorical Variables with LLMs: An Application to Labor Market Mismatch," NBER Working Papers, National Bureau of Economic Research, Inc, number 32327, Apr.
• Damir Filipović & Markus Pelger & Ye Ye, 2024, "Shrinking the Term Structure," NBER Working Papers, National Bureau of Economic Research, Inc, number 32472, May.
• Antoine Didisheim & Shikun (Barry) Ke & Bryan T. Kelly & Semyon Malamud, 2024, "APT or “AIPT”? The Surprising Dominance of Large Factor Models," NBER Working Papers, National Bureau of Economic Research, Inc, number 33012, Sep.
• Ruslan Goyenko & Bryan T. Kelly & Tobias J. Moskowitz & Yinan Su & Chao Zhang, 2024, "Trading Volume Alpha," NBER Working Papers, National Bureau of Economic Research, Inc, number 33037, Oct.
• Rui Da & Stefan Nagel & Dacheng Xiu, 2024, "The Statistical Limit of Arbitrage," NBER Working Papers, National Bureau of Economic Research, Inc, number 33070, Oct.
• Yue Cao & Judith A. Chevalier & Jessie Handbury & Hayden Parsley & Kevin R. Williams, 2024, "Willingness to Travel with Endogenous Distance: Evidence from the Changing Retail Landscape," NBER Working Papers, National Bureau of Economic Research, Inc, number 33307, Dec.
• Sebastian Bell & Ali Kakhbod & Martin Lettau & Abdolreza Nazemi, 2024, "Glass Box Machine Learning and Corporate Bond Returns," NBER Working Papers, National Bureau of Economic Research, Inc, number 33320, Dec.
• Mirko Djukic, 2024, "Topic classification of economic newspaper articles in a highly inflectional language – the case of Serbia," Working Papers Bulletin, National Bank of Serbia, number 21, Mar.
• O. Bonnet & F. Le Grand & T. Olivia & X. Ragot & L.Wilner, 2024, "The consumption response to unemployment : Evidence from French bank account data," Documents de Travail de l'Insee - INSEE Working Papers, Institut National de la Statistique et des Etudes Economiques, number 2024-23.
• Konstantin Kolev & Maya Tsoklinova, 2024, "The Impact of Consumer Loan Volume on Gross Fixed Capital Formation in Bulgaria: A Vector Error Correction Model (VECM) Approach," Godishnik na UNSS, University of National and World Economy, Sofia, Bulgaria, issue 1, pages 103-116, October.
• Graham Pilgrim & Shirly Ang, 2024, "The OECD-UNSD Multinational Enterprise Information Platform," OECD Statistics Working Papers, OECD Publishing, number 2024/01, Feb, DOI: 10.1787/b7d90a06-en.
• Graham Pilgrim & Emmanuelle Guidetti & Annabelle Mourougane, 2024, "An ocean of data: The potential of data on vessel traffic," OECD Statistics Working Papers, OECD Publishing, number 2024/02, Mar, DOI: 10.1787/34b7a926-en.
• Ștefan RUSU & Marcel BOLOȘ, 2024, "Machine Learning Clustering In Financial Markets: A Literature Review," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, volume 33, issue 1, pages 330-336, July.
• Thiemo Fetzer & Ludovica Gazze & Menna Bishop, 2024, "Distributional and climate implications of policy responses to energy price shocks," Economic Policy, CEPR, CESifo, Sciences Po;CES;MSH, volume 39, issue 120, pages 711-756.
• Tae-Hwy Lee & Ekaterina Seregina, 2024, "Optimal Portfolio Using Factor Graphical Lasso," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 3, pages 670-695.
• Luca Mucciante & Alessio Sancetta, 2024, "Estimation of an Order Book Dependent Hawkes Process for Large Datasets," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 4, pages 1098-1129.
• Leonardo Bargigli & Giulio Cifarelli, 2024, "Endogenous Volatility in the Foreign Exchange Market," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 4, pages 773-807.
• Minseog Oh & Donggyu Kim, 2024, "Effect of the U.S.–China Trade War on Stock Markets: A Financial Contagion Perspective," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 4, pages 954-1005.
• Donggyu Kim & Minseog Oh & Xinyu Song & Yazhen Wang, 2024, "Factor Overnight GARCH-Itô Models," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 5, pages 1209-1235.
• Rasmus Lönn & Peter C Schotman, 2024, "Empirical Asset Pricing with Many Test Assets," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 5, pages 1236-1263.
• Massimiliano Caporin & Tommaso Di Fonzo & Daniele Girolimetto, 2024, "Exploiting Intraday Decompositions in Realized Volatility Forecasting: A Forecast Reconciliation Approach," Journal of Financial Econometrics, Oxford University Press, volume 22, issue 5, pages 1759-1784.
• Anastasios Kagkadis & Ingmar Nolte & Sandra Nolte & Nikolaos Vasilas, 2024, "Factor Timing with Portfolio Characteristics," The Review of Asset Pricing Studies, Society for Financial Studies, volume 14, issue 1, pages 84-118.
• Yufeng Han & Ai He & David E Rapach & Guofu Zhou, 2024, "Cross-sectional expected returns: new Fama–MacBeth regressions in the era of machine learning," Review of Finance, European Finance Association, volume 28, issue 6, pages 1807-1831.
• Mihai Ciobotea & Marian Stan, 2024, "European Perspectives on Datafication," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, volume 0, issue 1, pages 175-183, August.
• Alina Bobasu & Lucia Quaglietti & Martino Ricci, 2024, "Tracking Global Economic Uncertainty: Implications for the Euro Area," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, volume 72, issue 2, pages 820-857, June, DOI: 10.1057/s41308-023-00216-9.
• Yi Chen & Hanming Fang & Yi Zhao & Zibo Zhao, 2024, "Recovering Overlooked Information in Categorical Variables with LLMs: An Application to Labor Market Mismatch," PIER Working Paper Archive, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, number 24-017, Jul.
• Nwaobi, Godwin, 2024, "Productive Sectors and Digital Diffusion(Adoption) in Nigeria: Empirical Evidence," MPRA Paper, University Library of Munich, Germany, number 122392, Oct.
• Kox, Henk L.M., 2024, "Towards time-consistent bilateral FDI statistics: A new dataset covering 2001-2022," MPRA Paper, University Library of Munich, Germany, number 122883, Oct.
• Yunus Karaömer & Arif Eser Guzel, 2024, "Effect of Economic Policy Uncertainty on Stock Returns: Analysing the Moderating Role of Government Size," Politická ekonomie, Prague University of Economics and Business, volume 2024, issue 1, pages 50-72, DOI: 10.18267/j.polek.1407.
• João Amador & Paulo Barbosa & João Cortes, 2024, "Distance to Export: A Machine Learning Approach with Portuguese Firms," Working Papers, Banco de Portugal, Economics and Research Department, number w202420.
• Luke Hartigan & Tom Rosewall, 2024, "Nowcasting Quarterly GDP Growth during the COVID-19 Crisis Using a Monthly Activity Indicator," RBA Research Discussion Papers, Reserve Bank of Australia, number rdp2024-04, Jul, DOI: 10.47688/rdp2024-04.
• Alok Raj & Rajeev Ranjan Kumar & Anand Jeyaraj, 2024, "Antecedents and Outcomes of Big Data Adoption in Supply Chain: A Meta-Analytic Investigation," American Business Review, Pompea College of Business, University of New Haven, volume 27, issue 2, pages 775-797.
• Morteza Beiranvand & Seyed Saeed Malek Sadati & Seyed Mohammad Javad Razmi, 2024, "Nowcasting Iran's GDP Using Sentiment Analysis of Economic News," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, volume 11, issue 3, pages 135-164.
• Fedor O. Chernenkov & Omer Allagabo Omer Mustafa, 2024, "Benefits of Big Data in the Financial Sector and Financial Stability Risks," Economic Consultant, Scientific and Educational Initiative LLC, issue 3, pages 30-43, September, DOI: 10.46224/ecoc.2024.3.3.
• Vlad TEODORESCU & Catalina-Ioana TOADER, 2024, "Using Machine Learning to Model Bankruptcy Risk in Listed Companies," PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ECONOMICS AND SOCIAL SCIENCES, Bucharest University of Economic Studies, Romania, volume 6, issue 1, pages 610-619, August.
• Alexandra-Cristina-Daniela CIUVERCA, 2024, "Sentiment Analysis of Research on AI Ethics: A Web-Based Study," PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ECONOMICS AND SOCIAL SCIENCES, Bucharest University of Economic Studies, Romania, volume 6, issue 1, pages 672-681, August.
• Nicola Caravaggio, 2024, "A first impact evaluation of the Italian Dignity Decree’s effects on young workers," Departmental Working Papers of Economics - University 'Roma Tre', Department of Economics - University Roma Tre, number 0280, Mar.
• Riccardo Di Francesco, 2024, "Ordered Correlation Forest," CEIS Research Paper, Tor Vergata University, CEIS, number 577, May, revised 06 May 2024.
• Chayanika Mitra, 2024, "Gender Bias in Education Expenditure among Religious and Social Groups: A Case Study for Below Class 10 Level in West Bengal," Arthaniti: Journal of Economic Theory and Practice, , volume 23, issue 1, pages 101-117, June, DOI: 10.1177/09767479211046400.
• Christopher F. Baum & Hans Lööf & Andreas Stephan & Klaus F. Zimmermann, 2024, "Estimating the Wage Premia of Refugee Immigrants: Lessons from Sweden," ILR Review, Cornell University, ILR School, volume 77, issue 4, pages 562-597, August, DOI: 10.1177/00197939241261640.
• Milen Arro-Cannarsa & Rolf Scheufele, 2024, "Nowcasting GDP: what are the gains from machine learning algorithms?," Working Papers, Swiss National Bank, number 2024-06.
• Francesco Audrino & Jessica Gentner & Simon Stalder, 2024, "Quantifying uncertainty: a new era of measurement through large language models," Working Papers, Swiss National Bank, number 2024-12.
• Aurel Ruben Mäder & Matthias Jüttner & Daniel Gatica-Perez, 2024, "You are how you pay: understanding and identifying the payment behavior of sociodemographic groups," Working Papers, Swiss National Bank, number 2024-13.
• Gustavo Romero Cardoso & Marcio Issao Nakane, 2024, "What's in a headline? News impact on the Brazilian economy," Working Papers, Department of Economics, University of São Paulo (FEA-USP), number 2024_12, Apr.
• Nikola Gradojevic & Dragan Kukolj, 2024, "Unlocking the black box: Non-parametric option pricing before and during COVID-19," Annals of Operations Research, Springer, volume 334, issue 1, pages 59-82, March, DOI: 10.1007/s10479-022-04578-7.
• Marc-Aurèle Divernois & Damir Filipović, 2024, "StockTwits classified sentiment and stock returns," Digital Finance, Springer, volume 6, issue 2, pages 249-281, June, DOI: 10.1007/s42521-023-00102-z.
• Axel Groß-Klußmann, 2024, "Learning deep news sentiment representations for macro-finance," Digital Finance, Springer, volume 6, issue 3, pages 341-377, September, DOI: 10.1007/s42521-024-00107-2.
• Aleksandar Kešeljević & Rok Spruk, 2024, "Estimating the effects of Syrian civil war," Empirical Economics, Springer, volume 66, issue 2, pages 671-703, February, DOI: 10.1007/s00181-023-02470-2.
• Massimiliano Caporin & C. Vladimir Rodríguez-Caballero & Esther Ruiz, 2024, "The factor structure of exchange rates volatility: global and intermittent factors," Empirical Economics, Springer, volume 67, issue 1, pages 31-45, July, DOI: 10.1007/s00181-023-02542-3.
• Dohyun Chun & Jongho Kang & Jihun Kim, 2024, "Forecasting returns with machine learning and optimizing global portfolios: evidence from the Korean and U.S. stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, volume 10, issue 1, pages 1-30, December, DOI: 10.1186/s40854-024-00648-w.
• André Nunes Maranhão, 2024, "Brazilian Business Cycle Analysis in a High-Dimensional and Time-Irregular Span Context," Journal of Business Cycle Research, Springer;Centre for International Research on Economic Tendency Surveys (CIRET), volume 20, issue 1, pages 1-58, August, DOI: 10.1007/s41549-024-00095-7.
• Meilian Zhang & Ting Yin & Emiko Usui & Takashi Oshio & Yi Zhang, 2024, "Unraveling the determinants of overemployment and underemployment among older workers in Japan: A machine learning approach," The Japanese Economic Review, Springer, volume 75, issue 4, pages 691-737, December, DOI: 10.1007/s42973-024-00173-6.